Dean Wu

89 papers receiving 1.6k citations

Peers

Dean Wu
Comparison fields: 5 of 152
  • Endocrine and Autonomic Systems 260
  • Management Information Systems 213
  • Experimental and Cognitive Psychology 266
  • Neurology 233
  • Physiology 382
Replace Giuseppe Micieli with:
Giuseppe Micieli Italy
Christopher H. Morrell United States
Charles André Brazil
D. Lyons United Kingdom
Ying Ma China
Christopher W. Myers United States
Andrew J. Shepherd United States
Tamara Hayes United States
Christian Binder Denmark
Shirley Coleman United Kingdom
Dean Wu relative to Giuseppe Micieli Italy Giuseppe Micieli's profile →
Citations per field
00.5×4.0×
Giuseppe Micieli · 1×
Citations per year

Countries citing papers authored by Dean Wu

Since Specialization
Citations

This map shows the geographic impact of Dean Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dean Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dean Wu more than expected).

Fields of papers citing papers by Dean Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dean Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dean Wu. The network helps show where Dean Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Dean Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dean Wu Line = papers co-authored together Dean Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005213
2 202097
3 202179
4 202176
5 196152
6 202047
7 201643
8 201942
9 201340
10 201839
11 201735
12 201335
13 201933
14 201533
15 201330
16 201929
17 201229
18 202027
19 201927
20 201526

About Dean Wu

Dean Wu is a scholar working on Physiology, Cognitive Neuroscience, Endocrine and Autonomic Systems, Experimental and Cognitive Psychology and Epidemiology, having authored 92 papers that have together received 1.7k indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (18 papers), Sleep and Wakefulness Research (18 papers), Neuroscience of respiration and sleep (14 papers), Sleep and related disorders (13 papers), Parkinson's Disease Mechanisms and Treatments (8 papers), Advanced Queuing Theory Analysis (6 papers), Circadian rhythm and melatonin (5 papers) and Air Quality and Health Impacts (5 papers). The work is most often cited by research in Endocrine and Autonomic Systems (260 citations), Management Information Systems (213 citations), Experimental and Cognitive Psychology (266 citations), Neurology (233 citations) and Physiology (382 citations). Dean Wu has collaborated with scholars based in Taiwan, United Kingdom and China. Frequent co-authors include Hideaki Takagi, Chaur‐Jong Hu, Chien‐Tai Hong, Wen‐Te Liu, Hsin‐Chien Lee, Lung Chan, Faizul Hasan, Nai‐Fang Chi, Christopher J. Gordon and Jer-Nan Juang. Their work appears in journals such as Frontiers in Neurology, Journal of the Neurological Sciences, The Science of The Total Environment, Sensors and Journal of Clinical Sleep Medicine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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